Job descriptionDiscover the Opportunity:We're partnering with a leading financial services organisation in Abu Dhabi that is continuing to scale its advanced analytics and AI capabilities.This role sits within a high-impact AI and product analytics team, focused on delivering production-grade machine learning solutions that drive data-led decision-making across the business.You will play a key role in translating complex business challenges into scalable data science solutions, working closely with product, engineering, and architecture teams to deliver real-world impact.This is a highly hands-on position suited to a technically strong data scientist who enjoys owning the full lifecycle of AI use cases while contributing to best practices across modelling, experimentation, and MLOps.Discover the Responsibilities:Translate complex business problems into structured analytical and machine learning solutions, defining hypotheses, success metrics, and validation strategies.Lead the design and development of advanced statistical, machine learning, and NLP models to solve high-impact use cases.Own the end-to-end data science lifecycle, including data exploration, feature engineering, model development, validation, and deployment.Conduct rigorous experimentation using cross-validation, back-testing, and statistical analysis to continuously improve model performance.Collaborate with data engineering teams to ensure high-quality, scalable data pipelines and curated datasets for production use.Support model deployment using APIs, batch, or streaming approaches, ensuring scalability, performance, and security.Monitor model performance, data drift, and reliability, implementing retraining strategies and lifecycle management processes.Ensure models meet interpretability, fairness, and regulatory standards within a governed environment.Contribute to code quality, reusability, documentation standards, and continuous improvement of team practices.Support model governance, documentation, and audit readiness, ensuring compliance with internal and regulatory frameworks.Discover the Requirements:8+ years of experience delivering end-to-end data science and machine learning solutions in production environments.Strong hands-on expertise in Python (e.g. pandas, NumPy) and SQL, with experience writing clean, production-ready code.Strong foundation in statistics, experimentation, and analytical techniques, including hypothesis testing and A/B testing.Experience with supervised and unsupervised machine learning, feature engineering, model selection, and performance optimisation.Experience working with large datasets, including data preparation, EDA, and insight generation.Experience deploying and maintaining models in production, including monitoring, retraining, and lifecycle management.Strong understanding of MLOps practices and working within CI/CD-driven environments.Experience working in regulated or data-governed environments is highly preferred.Strong stakeholder management skills, with the ability to communicate complex insights to both technical and non-technical audiences.Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
